Many Chemistry-Climate Models (CCMs) include a simplified treatment of brominated very short-lived (VSL) species by assuming CHBr as a surrogate for VSL. However, neglecting a comprehensive treatment of VSL in CCMs may yield an unrealistic representation of the associated impacts. Here, we use the Community Atmospheric Model with Chemistry (CAM-Chem) CCM to quantify the tropospheric and stratospheric changes between various VSL chemical approaches with increasing degrees of complexity (i.
View Article and Find Full Text PDFFour monitoring campaigns between the years 2009 and 2018 were conducted in Córdoba City, Argentina, to detect toxic metals in PM2.5 samples. The concentrations of As, Cd, Pb, Cu, Cr, Mn, Hg, Ni, and Zn, together with several other elements, were measured.
View Article and Find Full Text PDFAccurate estimates of total global solar irradiance reaching the Earth's surface are relevant since routine measurements are not always available. This work aimed to determine which of the models used to estimate daily total global solar irradiance (TGSI) is the best model when irradiance measurements are scarce in a given site. A model based on an artificial neural network (ANN) and empirical models based on temperature and sunshine measurements were analyzed and evaluated in Córdoba, Argentina.
View Article and Find Full Text PDFIn Argentina no historical or present programs exist specifically assessing ecosystem health with respect to photochemical air pollution, although phytotoxic concentrations of near-ground ozone have been documented in recent years. Here we report our preliminary findings on field observations of ozone-like injury found in natural plant populations and agroecosystems late in the 2005 growing season in the Southern Hemisphere. Several possible ozone bioindicator plants which have not been previously documented were observed to exhibit foliar symptoms consistent with ozone-induced injury.
View Article and Find Full Text PDFA simple method is presented for estimating hourly distribution of air pollutants, based on data collected by passive sensors on a weekly or bi-weekly basis with no need for previous measurements at a site. In order for this method to be applied to locations where no hourly records are available, reference data from other sites are required to generate calibration histograms. The proposed procedure allows one to obtain the histogram of hourly ozone values during a given week with an error of about 30%, which is good considering the simplicity of this approach.
View Article and Find Full Text PDFThis paper presents a technique based on artificial neural networks (ANN) to estimate pollutant rates of emission from industrial stacks, on the basis of pollutant concentrations measured on the ground. The ANN is trained on data generated by the ISCST3 model, widely accepted for evaluation of dispersion of primary pollutants as a part of an environmental impact study. Simulations using theoretical values and comparison with field data are done, obtaining good results in both cases at predicting emission rates.
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